1. Technical Field
The present invention relates in general to expert systems and, in particular, to case-based reasoning systems. Still more particularly, the present invention relates to a case-based reasoning system and method of scoring cases in a case database.
2. Description of the Related Art
A case-based reasoning (CBR) system generally refers to a computer system that identifies a solution to a current problem by examining descriptions of similar, previously encountered problems and their associated solutions, matching the current problem with one or more similar previously encountered problems, and using the associated solutions of the matching previously encountered problems to suggest a solution to the current problem. In response to receipt of a description of a current problem, a conventional CBR system retrieves the closest matching cases from a case database using a search engine and iteratively prompts the user for additional descriptive information until the retrieved case or cases identified by the search engine are sufficiently similar to the current problem to be considered as possible solutions. If a new solution (not previously stored in the case database) is subsequently validated, the validated solution can be entered into the case database and utilized to solve future problems.
Of course, the quality of solutions produced by a CBR system will depend, in part, upon the method utilized by the search engine to determine the best matching case in the case database. Conventional case-based reasoning systems assign scores to each case in the case database and select the highest scoring case as the best matching case. Current scoring methods tend to be complex, however, resulting in poor system performance, particularly when the case database contains a large number of cases or cases having a large number of attributes.
As should thus be apparent, it would be desirable from a performance standpoint to provide an improved method and system for scoring cases in the case database of a CBR system.